Estimating the position of multiple targets with one or more sensor requires assignment measurements to tracks
A track is defined as the unique path of a distinct object. In situations where there are a multiple objects, such as for a radar system in a car during rush hour traffic, it is necessary to associate measurements with objects.
Track Oriented Multiple Hypothesis Testing is a powerful technique for assigning measurements to tracks of objects when the number of objects is unknown or changing. It is absolutely essential for accurate tracking of multiple objects.
Tracking is based on the formulation of hypotheses. Hypotheses are sets of tracks with consistent data, that is, where no measurements are assigned to more than one track.
The track-oriented approach recomputes the hypotheses using the newly updated tracks after each scan of data is received. Rather than maintaining, and expanding, hypotheses from scan to scan, the track-oriented approach discards the hypotheses formed on scan $k-1$. The tracks that survive pruning are propagated to the next scan k where new tracks are formed, using the new observations, and reformed into hypotheses. Except for the necessity to delete some tracks based upon low probability, no information is lost because the track scores, that are maintained, contain all the relevant statistical data.
Hypotheses are sets of tracks with consistent data, that is, where no measurements are assigned to more than one track. The track-oriented approach recomputes the hypotheses using the newly updated tracks after each scan of data is received. Rather than maintaining, and expanding, hypotheses from scan to scan, the track-oriented approach discards the hypotheses formed on scan k−1. The tracks that survive pruning are propagated to the next scan k where new tracks are formed, using the new observations, and reformed into hypotheses. Except for the necessity to delete some tracks based upon low probability, no information is lost because the track scores, that are maintained, contain all the relevant statistical data.
Ding, et. al, U.S. Pat. No. 7,626,535, Dec. 1, 2009, “Track Quality Based Multi-Target Tracker,” discloses a track based multi-target tracking system. Their method does not allow for multiple sensors and provides not mechanism for multiple sensors. This application improves on their patent by providing a rigorous method for using mulitple sensors and a more robust tracking algorithm.
Carson, et. al, U.S. Pat. No. 5,379,044, Jan. 3, 1995, “Efficient Multi-Target Tracking System,” cannot be adapted to multiple-sensors. In addition, this application improves on its processing method by using integer programming which is far more efficient than the disclosed algorithm.
Miller, U.S. Pat. No. 4,072,943, Feb. 7, 1978, “Multi-Target Tracking” provides no mechanism for associating measurements with multi-targets nor can it be added to the disclosed system.
The cited patents for tracking targets do not solve the fundamental problem of assigning multiple measurements to multiple objects when the objects are observed by multiple sensors.